A novel identification method for generalized T-S fuzzy systems
Journal article, Peer reviewed
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http://hdl.handle.net/11250/136928Utgivelsesdato
2012Metadata
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Originalversjon
Huang, L., Wang, K., Shi, P., & Karimi, H.R. (2012). A novel identification method for generalized T-S fuzzy systems. Mathematical Problems in Engineering, 2012. doi: 10.1155/2012/893807 10.1155/2012/893807Sammendrag
In order to approximate any nonlinear system, not just affine nonlinear systems, generalized T-S fuzzy systems, where the control variables and the state variables, are all premise variables are introduced in the paper. Firstly, fuzzy spaces and rules were determined by using ant colony algorithm. Secondly, the state-space model parameters are identified by using genetic algorithm. The simulation results show the effectiveness of the proposed algorithm
Beskrivelse
Published version of an article from the journal: Mathematical Problems in Engineering. Also available from the publisher:http://dx.doi.org/10.1155/2012/893807